{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2 \n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras.backend.tensorflow_backend as KTF\n",
    "import tensorflow as tf\n",
    "config = tf.ConfigProto()  \n",
    "config.gpu_options.allow_growth=True   \n",
    "session = tf.Session(config=config)\n",
    "KTF.set_session(session)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import keras \n",
    "from models.psenet import psenet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "shape = (None,None,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files\\Anaconda3\\lib\\site-packages\\keras_applications\\resnet50.py:265: UserWarning: The output shape of `ResNet50(include_top=False)` has been changed since Keras 2.2.0.\n",
      "  warnings.warn('The output shape of `ResNet50(include_top=False)` '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, None, None, 3 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lambda_1 (Lambda)               (None, None, None, 3 0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv1_pad (ZeroPadding2D)       (None, None, None, 3 0           lambda_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1 (Conv2D)                  (None, None, None, 6 9472        conv1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "bn_conv1 (BatchNormalization)   (None, None, None, 6 256         conv1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, None, None, 6 0           bn_conv1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "pool1_pad (ZeroPadding2D)       (None, None, None, 6 0           activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, None, None, 6 0           pool1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2a (Conv2D)         (None, None, None, 6 4160        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2a (BatchNormalizati (None, None, None, 6 256         res2a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, None, None, 6 0           bn2a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2b (Conv2D)         (None, None, None, 6 36928       activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2b (BatchNormalizati (None, None, None, 6 256         res2a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, None, None, 6 0           bn2a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2c (Conv2D)         (None, None, None, 2 16640       activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch1 (Conv2D)          (None, None, None, 2 16640       max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2c (BatchNormalizati (None, None, None, 2 1024        res2a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch1 (BatchNormalizatio (None, None, None, 2 1024        res2a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, None, None, 2 0           bn2a_branch2c[0][0]              \n",
      "                                                                 bn2a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, None, None, 2 0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2a (Conv2D)         (None, None, None, 6 16448       activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2a (BatchNormalizati (None, None, None, 6 256         res2b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, None, None, 6 0           bn2b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2b (Conv2D)         (None, None, None, 6 36928       activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2b (BatchNormalizati (None, None, None, 6 256         res2b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, None, None, 6 0           bn2b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2c (Conv2D)         (None, None, None, 2 16640       activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2c (BatchNormalizati (None, None, None, 2 1024        res2b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, None, None, 2 0           bn2b_branch2c[0][0]              \n",
      "                                                                 activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, None, None, 2 0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2a (Conv2D)         (None, None, None, 6 16448       activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2a (BatchNormalizati (None, None, None, 6 256         res2c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, None, None, 6 0           bn2c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2b (Conv2D)         (None, None, None, 6 36928       activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2b (BatchNormalizati (None, None, None, 6 256         res2c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, None, None, 6 0           bn2c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2c (Conv2D)         (None, None, None, 2 16640       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2c (BatchNormalizati (None, None, None, 2 1024        res2c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, None, None, 2 0           bn2c_branch2c[0][0]              \n",
      "                                                                 activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, None, None, 2 0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2a (Conv2D)         (None, None, None, 1 32896       activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2a (BatchNormalizati (None, None, None, 1 512         res3a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, None, None, 1 0           bn3a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2b (Conv2D)         (None, None, None, 1 147584      activation_11[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2b (BatchNormalizati (None, None, None, 1 512         res3a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, None, None, 1 0           bn3a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2c (Conv2D)         (None, None, None, 5 66048       activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch1 (Conv2D)          (None, None, None, 5 131584      activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2c (BatchNormalizati (None, None, None, 5 2048        res3a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch1 (BatchNormalizatio (None, None, None, 5 2048        res3a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, None, None, 5 0           bn3a_branch2c[0][0]              \n",
      "                                                                 bn3a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, None, None, 5 0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2a (Conv2D)         (None, None, None, 1 65664       activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2a (BatchNormalizati (None, None, None, 1 512         res3b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, None, None, 1 0           bn3b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2b (Conv2D)         (None, None, None, 1 147584      activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2b (BatchNormalizati (None, None, None, 1 512         res3b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, None, None, 1 0           bn3b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2c (Conv2D)         (None, None, None, 5 66048       activation_15[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2c (BatchNormalizati (None, None, None, 5 2048        res3b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, None, None, 5 0           bn3b_branch2c[0][0]              \n",
      "                                                                 activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, None, None, 5 0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2a (Conv2D)         (None, None, None, 1 65664       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2a (BatchNormalizati (None, None, None, 1 512         res3c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, None, None, 1 0           bn3c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2b (Conv2D)         (None, None, None, 1 147584      activation_17[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2b (BatchNormalizati (None, None, None, 1 512         res3c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, None, None, 1 0           bn3c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2c (Conv2D)         (None, None, None, 5 66048       activation_18[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2c (BatchNormalizati (None, None, None, 5 2048        res3c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, None, None, 5 0           bn3c_branch2c[0][0]              \n",
      "                                                                 activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, None, None, 5 0           add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2a (Conv2D)         (None, None, None, 1 65664       activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2a (BatchNormalizati (None, None, None, 1 512         res3d_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, None, None, 1 0           bn3d_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2b (Conv2D)         (None, None, None, 1 147584      activation_20[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2b (BatchNormalizati (None, None, None, 1 512         res3d_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, None, None, 1 0           bn3d_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2c (Conv2D)         (None, None, None, 5 66048       activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2c (BatchNormalizati (None, None, None, 5 2048        res3d_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_7 (Add)                     (None, None, None, 5 0           bn3d_branch2c[0][0]              \n",
      "                                                                 activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, None, None, 5 0           add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2a (Conv2D)         (None, None, None, 2 131328      activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2a (BatchNormalizati (None, None, None, 2 1024        res4a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, None, None, 2 0           bn4a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2b (Conv2D)         (None, None, None, 2 590080      activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2b (BatchNormalizati (None, None, None, 2 1024        res4a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, None, None, 2 0           bn4a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2c (Conv2D)         (None, None, None, 1 263168      activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch1 (Conv2D)          (None, None, None, 1 525312      activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2c (BatchNormalizati (None, None, None, 1 4096        res4a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch1 (BatchNormalizatio (None, None, None, 1 4096        res4a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_8 (Add)                     (None, None, None, 1 0           bn4a_branch2c[0][0]              \n",
      "                                                                 bn4a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, None, None, 1 0           add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2a (Conv2D)         (None, None, None, 2 262400      activation_25[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2a (BatchNormalizati (None, None, None, 2 1024        res4b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, None, None, 2 0           bn4b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2b (Conv2D)         (None, None, None, 2 590080      activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2b (BatchNormalizati (None, None, None, 2 1024        res4b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, None, None, 2 0           bn4b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2c (Conv2D)         (None, None, None, 1 263168      activation_27[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2c (BatchNormalizati (None, None, None, 1 4096        res4b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_9 (Add)                     (None, None, None, 1 0           bn4b_branch2c[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, None, None, 1 0           add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2a (Conv2D)         (None, None, None, 2 262400      activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2a (BatchNormalizati (None, None, None, 2 1024        res4c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, None, None, 2 0           bn4c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2b (Conv2D)         (None, None, None, 2 590080      activation_29[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2b (BatchNormalizati (None, None, None, 2 1024        res4c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, None, None, 2 0           bn4c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2c (Conv2D)         (None, None, None, 1 263168      activation_30[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2c (BatchNormalizati (None, None, None, 1 4096        res4c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_10 (Add)                    (None, None, None, 1 0           bn4c_branch2c[0][0]              \n",
      "                                                                 activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, None, None, 1 0           add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2a (Conv2D)         (None, None, None, 2 262400      activation_31[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2a (BatchNormalizati (None, None, None, 2 1024        res4d_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, None, None, 2 0           bn4d_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2b (Conv2D)         (None, None, None, 2 590080      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2b (BatchNormalizati (None, None, None, 2 1024        res4d_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, None, None, 2 0           bn4d_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2c (Conv2D)         (None, None, None, 1 263168      activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2c (BatchNormalizati (None, None, None, 1 4096        res4d_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_11 (Add)                    (None, None, None, 1 0           bn4d_branch2c[0][0]              \n",
      "                                                                 activation_31[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, None, None, 1 0           add_11[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2a (Conv2D)         (None, None, None, 2 262400      activation_34[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2a (BatchNormalizati (None, None, None, 2 1024        res4e_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_35 (Activation)      (None, None, None, 2 0           bn4e_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2b (Conv2D)         (None, None, None, 2 590080      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2b (BatchNormalizati (None, None, None, 2 1024        res4e_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_36 (Activation)      (None, None, None, 2 0           bn4e_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2c (Conv2D)         (None, None, None, 1 263168      activation_36[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2c (BatchNormalizati (None, None, None, 1 4096        res4e_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_12 (Add)                    (None, None, None, 1 0           bn4e_branch2c[0][0]              \n",
      "                                                                 activation_34[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_37 (Activation)      (None, None, None, 1 0           add_12[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2a (Conv2D)         (None, None, None, 2 262400      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2a (BatchNormalizati (None, None, None, 2 1024        res4f_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, None, None, 2 0           bn4f_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2b (Conv2D)         (None, None, None, 2 590080      activation_38[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2b (BatchNormalizati (None, None, None, 2 1024        res4f_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, None, None, 2 0           bn4f_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2c (Conv2D)         (None, None, None, 1 263168      activation_39[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2c (BatchNormalizati (None, None, None, 1 4096        res4f_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_13 (Add)                    (None, None, None, 1 0           bn4f_branch2c[0][0]              \n",
      "                                                                 activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, None, None, 1 0           add_13[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2a (Conv2D)         (None, None, None, 5 524800      activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2a (BatchNormalizati (None, None, None, 5 2048        res5a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, None, None, 5 0           bn5a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2b (Conv2D)         (None, None, None, 5 2359808     activation_41[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2b (BatchNormalizati (None, None, None, 5 2048        res5a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_42 (Activation)      (None, None, None, 5 0           bn5a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2c (Conv2D)         (None, None, None, 2 1050624     activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch1 (Conv2D)          (None, None, None, 2 2099200     activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2c (BatchNormalizati (None, None, None, 2 8192        res5a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch1 (BatchNormalizatio (None, None, None, 2 8192        res5a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_14 (Add)                    (None, None, None, 2 0           bn5a_branch2c[0][0]              \n",
      "                                                                 bn5a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, None, None, 2 0           add_14[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2a (Conv2D)         (None, None, None, 5 1049088     activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2a (BatchNormalizati (None, None, None, 5 2048        res5b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, None, None, 5 0           bn5b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2b (Conv2D)         (None, None, None, 5 2359808     activation_44[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2b (BatchNormalizati (None, None, None, 5 2048        res5b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_45 (Activation)      (None, None, None, 5 0           bn5b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2c (Conv2D)         (None, None, None, 2 1050624     activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2c (BatchNormalizati (None, None, None, 2 8192        res5b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_15 (Add)                    (None, None, None, 2 0           bn5b_branch2c[0][0]              \n",
      "                                                                 activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_46 (Activation)      (None, None, None, 2 0           add_15[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2a (Conv2D)         (None, None, None, 5 1049088     activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2a (BatchNormalizati (None, None, None, 5 2048        res5c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_47 (Activation)      (None, None, None, 5 0           bn5c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2b (Conv2D)         (None, None, None, 5 2359808     activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2b (BatchNormalizati (None, None, None, 5 2048        res5c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, None, None, 5 0           bn5c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2c (Conv2D)         (None, None, None, 2 1050624     activation_48[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2c (BatchNormalizati (None, None, None, 2 8192        res5c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_16 (Add)                    (None, None, None, 2 0           bn5c_branch2c[0][0]              \n",
      "                                                                 activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, None, None, 2 0           add_16[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, None, None, 2 524544      activation_49[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_1 (resize_image)   (None, None, None, 2 0           conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, None, None, 2 262400      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, None, None, 5 0           resize_image_1[0][0]             \n",
      "                                                                 conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, None, None, 1 589952      concatenate_1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, None, None, 1 512         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_50 (Activation)      (None, None, None, 1 0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_2 (resize_image)   (None, None, None, 1 0           activation_50[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, None, None, 2 131328      activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_2 (Concatenate)     (None, None, None, 3 0           resize_image_2[0][0]             \n",
      "                                                                 conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, None, None, 1 442496      concatenate_2[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, None, None, 1 512         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_51 (Activation)      (None, None, None, 1 0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_3 (resize_image)   (None, None, None, 1 0           activation_51[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_3 (Concatenate)     (None, None, None, 3 0           resize_image_3[0][0]             \n",
      "                                                                 activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, None, None, 1 442496      concatenate_3[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, None, None, 1 512         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_52 (Activation)      (None, None, None, 1 0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_4 (resize_image)   (None, None, None, 1 0           activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_4 (Concatenate)     (None, None, None, 1 0           resize_image_4[0][0]             \n",
      "                                                                 activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, None, None, 1 221312      concatenate_4[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, None, None, 1 512         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_5 (resize_image)   (None, None, None, 2 0           conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_6 (resize_image)   (None, None, None, 1 0           activation_50[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_7 (resize_image)   (None, None, None, 1 0           activation_51[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_8 (resize_image)   (None, None, None, 1 0           activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_53 (Activation)      (None, None, None, 1 0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_5 (Concatenate)     (None, None, None, 7 0           resize_image_5[0][0]             \n",
      "                                                                 resize_image_6[0][0]             \n",
      "                                                                 resize_image_7[0][0]             \n",
      "                                                                 resize_image_8[0][0]             \n",
      "                                                                 activation_53[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, None, None, 2 1769728     concatenate_5[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, None, None, 2 1024        conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_54 (Activation)      (None, None, None, 2 0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, None, None, 6 1542        activation_54[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "resize_image_9 (resize_image)   (None, None, None, 6 0           conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_55 (Activation)      (None, None, None, 6 0           resize_image_9[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 27,976,582\n",
      "Trainable params: 27,921,926\n",
      "Non-trainable params: 54,656\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "inputs = keras.layers.Input(shape=shape)\n",
    "output = psenet(inputs)\n",
    "model  = keras.models.Model(inputs,output)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from keras.optimizers import Adam\n",
    "from models.loss import build_loss\n",
    "from models.metrics import build_iou,mean_iou\n",
    "from keras.utils import multi_gpu_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n",
      "(None, None)\n"
     ]
    }
   ],
   "source": [
    "parallel_model = multi_gpu_model(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "adam = Adam(1e-4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ious = build_iou([0,1],['bk','txt'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "parallel_model.compile(loss=build_loss,\n",
    "              optimizer=adam,\n",
    "              metrics=ious)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import config \n",
    "from tool.generator import Generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_dir = config.MIWI_2018_TRAIN_LABEL_DIR\n",
    "test_dir = config.MIWI_2018_TEST_LABEL_DIR\n",
    "batch_size = 4\n",
    "num_class =2 \n",
    "shape = (640,640)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gen_train = Generator(train_dir,batch_size = batch_size ,istraining=True,num_classes=num_class,mirror = False,reshape=shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gen_test = Generator(test_dir,batch_size = batch_size ,istraining=False,num_classes=num_class,\n",
    "                     reshape=shape,mirror=False,scale=False,clip=False,trans_color=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from keras.callbacks import ModelCheckpoint\n",
    "from keras.callbacks import TensorBoard\n",
    "checkpoint = ModelCheckpoint(r'resent50-190227_BLINEAR-{epoch:02d}.hdf5',\n",
    "                           save_weights_only=True)\n",
    "tb = TensorBoard(log_dir='./logs', update_freq=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/40\n",
      "  24/2255 [..............................] - ETA: 1:12:05 - loss: 0.4875 - iou_bk: 0.8008 - iou_txt: 0.4072"
     ]
    }
   ],
   "source": [
    "res = parallel_model.fit_generator(gen_train,\n",
    "                          steps_per_epoch =gen_train.num_samples()// batch_size,\n",
    "                          epochs = 40,\n",
    "                          validation_data=gen_test,\n",
    "                          validation_steps =gen_test.num_samples()//batch_size,\n",
    "                          verbose=1,\n",
    "                          initial_epoch=0,\n",
    "                          workers=4,\n",
    "                          max_queue_size=16,\n",
    "                          callbacks=[checkpoint,tb])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "parallel_model.optimizer.lr = 1e-5\n",
    "res = parallel_model.fit_generator(gen_train,\n",
    "                          steps_per_epoch =gen_train.num_samples()// batch_size,\n",
    "                          epochs = 70,\n",
    "                          validation_data=gen_test,\n",
    "                          validation_steps =gen_test.num_samples()//batch_size,\n",
    "                          verbose=1,\n",
    "                          initial_epoch=37,\n",
    "                          workers=4,\n",
    "                          max_queue_size=16,\n",
    "                          callbacks=[checkpoint,tb])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 71/150\n",
      "2255/2255 [==============================] - 2020s 896ms/step - loss: 0.0888 - iou_bk: 0.9682 - iou_txt: 0.8549 - val_loss: 0.0912 - val_iou_bk: 0.9673 - val_iou_txt: 0.8504\n",
      "Epoch 72/150\n",
      "2255/2255 [==============================] - 1989s 882ms/step - loss: 0.0878 - iou_bk: 0.9688 - iou_txt: 0.8565 - val_loss: 0.0895 - val_iou_bk: 0.9682 - val_iou_txt: 0.8525\n",
      "Epoch 73/150\n",
      "2255/2255 [==============================] - 1999s 886ms/step - loss: 0.0879 - iou_bk: 0.9690 - iou_txt: 0.8567 - val_loss: 0.0905 - val_iou_bk: 0.9675 - val_iou_txt: 0.8499\n",
      "Epoch 74/150\n",
      "2255/2255 [==============================] - 2019s 895ms/step - loss: 0.0898 - iou_bk: 0.9686 - iou_txt: 0.8532 - val_loss: 0.0920 - val_iou_bk: 0.9670 - val_iou_txt: 0.8502\n",
      "Epoch 75/150\n",
      "2255/2255 [==============================] - 1995s 884ms/step - loss: 0.0879 - iou_bk: 0.9686 - iou_txt: 0.8568 - val_loss: 0.0890 - val_iou_bk: 0.9681 - val_iou_txt: 0.8541\n",
      "Epoch 76/150\n",
      "2255/2255 [==============================] - 2003s 888ms/step - loss: 0.0872 - iou_bk: 0.9693 - iou_txt: 0.8579 - val_loss: 0.0901 - val_iou_bk: 0.9680 - val_iou_txt: 0.8526\n",
      "Epoch 77/150\n",
      "2255/2255 [==============================] - 2001s 888ms/step - loss: 0.0875 - iou_bk: 0.9691 - iou_txt: 0.8570 - val_loss: 0.0895 - val_iou_bk: 0.9679 - val_iou_txt: 0.8529\n",
      "Epoch 78/150\n",
      "2255/2255 [==============================] - 1998s 886ms/step - loss: 0.0882 - iou_bk: 0.9692 - iou_txt: 0.8558 - val_loss: 0.0883 - val_iou_bk: 0.9686 - val_iou_txt: 0.8546\n",
      "Epoch 79/150\n",
      "2255/2255 [==============================] - 1994s 884ms/step - loss: 0.0874 - iou_bk: 0.9688 - iou_txt: 0.8571 - val_loss: 0.0874 - val_iou_bk: 0.9689 - val_iou_txt: 0.8564\n",
      "Epoch 80/150\n",
      "2255/2255 [==============================] - 2015s 893ms/step - loss: 0.0867 - iou_bk: 0.9695 - iou_txt: 0.8587 - val_loss: 0.0897 - val_iou_bk: 0.9678 - val_iou_txt: 0.8535\n",
      "Epoch 81/150\n",
      "2255/2255 [==============================] - 1991s 883ms/step - loss: 0.0862 - iou_bk: 0.9696 - iou_txt: 0.8595 - val_loss: 0.0898 - val_iou_bk: 0.9679 - val_iou_txt: 0.8543\n",
      "Epoch 82/150\n",
      "2255/2255 [==============================] - 2005s 889ms/step - loss: 0.0856 - iou_bk: 0.9697 - iou_txt: 0.8604 - val_loss: 0.0903 - val_iou_bk: 0.9673 - val_iou_txt: 0.8521\n",
      "Epoch 83/150\n",
      "   1/2255 [..............................] - ETA: 25:03 - loss: 0.0611 - iou_bk: 0.9668 - iou_txt: 0.9080"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\callbacks.py:122: UserWarning: Method on_batch_end() is slow compared to the batch update (0.838847). Check your callbacks.\n",
      "  % delta_t_median)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2255/2255 [==============================] - 1997s 886ms/step - loss: 0.0885 - iou_bk: 0.9684 - iou_txt: 0.8555 - val_loss: 0.0876 - val_iou_bk: 0.9687 - val_iou_txt: 0.8558\n",
      "Epoch 84/150\n",
      "2255/2255 [==============================] - 2003s 888ms/step - loss: 0.0874 - iou_bk: 0.9696 - iou_txt: 0.8574 - val_loss: 0.0864 - val_iou_bk: 0.9694 - val_iou_txt: 0.8579\n",
      "Epoch 85/150\n",
      "2255/2255 [==============================] - 1991s 883ms/step - loss: 0.0850 - iou_bk: 0.9705 - iou_txt: 0.8616 - val_loss: 0.0856 - val_iou_bk: 0.9697 - val_iou_txt: 0.8587\n",
      "Epoch 86/150\n",
      "2255/2255 [==============================] - 1990s 883ms/step - loss: 0.0861 - iou_bk: 0.9694 - iou_txt: 0.8593 - val_loss: 0.0872 - val_iou_bk: 0.9683 - val_iou_txt: 0.8557\n",
      "Epoch 87/150\n",
      "2255/2255 [==============================] - 2021s 896ms/step - loss: 0.0861 - iou_bk: 0.9694 - iou_txt: 0.8597 - val_loss: 0.0903 - val_iou_bk: 0.9679 - val_iou_txt: 0.8536\n",
      "Epoch 88/150\n",
      "2255/2255 [==============================] - 2001s 887ms/step - loss: 0.0857 - iou_bk: 0.9701 - iou_txt: 0.8603 - val_loss: 0.0872 - val_iou_bk: 0.9686 - val_iou_txt: 0.8548\n",
      "Epoch 89/150\n",
      "2255/2255 [==============================] - 1993s 884ms/step - loss: 0.0858 - iou_bk: 0.9695 - iou_txt: 0.8600 - val_loss: 0.0871 - val_iou_bk: 0.9693 - val_iou_txt: 0.8564\n",
      "Epoch 90/150\n",
      "2255/2255 [==============================] - 1985s 880ms/step - loss: 0.0859 - iou_bk: 0.9698 - iou_txt: 0.8603 - val_loss: 0.0878 - val_iou_bk: 0.9685 - val_iou_txt: 0.8550\n",
      "Epoch 91/150\n",
      "2255/2255 [==============================] - 2021s 896ms/step - loss: 0.0849 - iou_bk: 0.9704 - iou_txt: 0.8614 - val_loss: 0.0912 - val_iou_bk: 0.9670 - val_iou_txt: 0.8488\n",
      "Epoch 92/150\n",
      "2255/2255 [==============================] - 1993s 884ms/step - loss: 0.0848 - iou_bk: 0.9703 - iou_txt: 0.8615 - val_loss: 0.0900 - val_iou_bk: 0.9675 - val_iou_txt: 0.8519\n",
      "Epoch 93/150\n",
      "   2/2255 [..............................] - ETA: 26:02 - loss: 0.0738 - iou_bk: 0.9758 - iou_txt: 0.8750"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\callbacks.py:122: UserWarning: Method on_batch_end() is slow compared to the batch update (0.987048). Check your callbacks.\n",
      "  % delta_t_median)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2255/2255 [==============================] - 2011s 892ms/step - loss: 0.0853 - iou_bk: 0.9699 - iou_txt: 0.8606 - val_loss: 0.0872 - val_iou_bk: 0.9693 - val_iou_txt: 0.8554\n",
      "Epoch 94/150\n",
      "2255/2255 [==============================] - 1987s 881ms/step - loss: 0.0836 - iou_bk: 0.9710 - iou_txt: 0.8640 - val_loss: 0.0851 - val_iou_bk: 0.9697 - val_iou_txt: 0.8589\n",
      "Epoch 95/150\n",
      "2255/2255 [==============================] - 2002s 888ms/step - loss: 0.0846 - iou_bk: 0.9702 - iou_txt: 0.8622 - val_loss: 0.0860 - val_iou_bk: 0.9692 - val_iou_txt: 0.8586\n",
      "Epoch 96/150\n",
      "2255/2255 [==============================] - 2007s 890ms/step - loss: 0.0857 - iou_bk: 0.9697 - iou_txt: 0.8602 - val_loss: 0.0937 - val_iou_bk: 0.9668 - val_iou_txt: 0.8511\n",
      "Epoch 97/150\n",
      "2255/2255 [==============================] - 1998s 886ms/step - loss: 0.0844 - iou_bk: 0.9705 - iou_txt: 0.8624 - val_loss: 0.0866 - val_iou_bk: 0.9694 - val_iou_txt: 0.8587\n",
      "Epoch 98/150\n",
      "2255/2255 [==============================] - 2003s 888ms/step - loss: 0.0842 - iou_bk: 0.9702 - iou_txt: 0.8626 - val_loss: 0.0888 - val_iou_bk: 0.9682 - val_iou_txt: 0.8542\n",
      "Epoch 99/150\n",
      "2255/2255 [==============================] - 1990s 883ms/step - loss: 0.0840 - iou_bk: 0.9703 - iou_txt: 0.8632 - val_loss: 0.0866 - val_iou_bk: 0.9691 - val_iou_txt: 0.8577\n",
      "Epoch 100/150\n",
      "2255/2255 [==============================] - 1981s 879ms/step - loss: 0.0841 - iou_bk: 0.9706 - iou_txt: 0.8633 - val_loss: 0.0874 - val_iou_bk: 0.9693 - val_iou_txt: 0.8567\n",
      "Epoch 101/150\n",
      "2255/2255 [==============================] - 2021s 896ms/step - loss: 0.0845 - iou_bk: 0.9701 - iou_txt: 0.8622 - val_loss: 0.0890 - val_iou_bk: 0.9682 - val_iou_txt: 0.8552\n",
      "Epoch 102/150\n",
      "2255/2255 [==============================] - 1988s 882ms/step - loss: 0.0840 - iou_bk: 0.9706 - iou_txt: 0.8633 - val_loss: 0.0849 - val_iou_bk: 0.9699 - val_iou_txt: 0.8604\n",
      "Epoch 103/150\n",
      "2255/2255 [==============================] - 1999s 886ms/step - loss: 0.0835 - iou_bk: 0.9707 - iou_txt: 0.8639 - val_loss: 0.0886 - val_iou_bk: 0.9673 - val_iou_txt: 0.8520\n",
      "Epoch 104/150\n",
      "2255/2255 [==============================] - 2006s 890ms/step - loss: 0.0846 - iou_bk: 0.9701 - iou_txt: 0.8620 - val_loss: 0.0850 - val_iou_bk: 0.9696 - val_iou_txt: 0.8597\n",
      "Epoch 105/150\n",
      "2255/2255 [==============================] - 1999s 886ms/step - loss: 0.0828 - iou_bk: 0.9706 - iou_txt: 0.8652 - val_loss: 0.0876 - val_iou_bk: 0.9687 - val_iou_txt: 0.8563\n",
      "Epoch 106/150\n",
      "2255/2255 [==============================] - 2010s 891ms/step - loss: 0.0828 - iou_bk: 0.9711 - iou_txt: 0.8654 - val_loss: 0.0859 - val_iou_bk: 0.9698 - val_iou_txt: 0.8593\n",
      "Epoch 107/150\n",
      "2255/2255 [==============================] - 1993s 884ms/step - loss: 0.0823 - iou_bk: 0.9710 - iou_txt: 0.8660 - val_loss: 0.0876 - val_iou_bk: 0.9684 - val_iou_txt: 0.8554\n",
      "Epoch 108/150\n",
      "2255/2255 [==============================] - 1988s 882ms/step - loss: 0.0829 - iou_bk: 0.9710 - iou_txt: 0.8652 - val_loss: 0.0871 - val_iou_bk: 0.9690 - val_iou_txt: 0.8565\n",
      "Epoch 109/150\n",
      "2255/2255 [==============================] - 2026s 899ms/step - loss: 0.0834 - iou_bk: 0.9702 - iou_txt: 0.8641 - val_loss: 0.0873 - val_iou_bk: 0.9687 - val_iou_txt: 0.8543\n",
      "Epoch 110/150\n",
      "1327/2255 [================>.............] - ETA: 12:35 - loss: 0.0845 - iou_bk: 0.9705 - iou_txt: 0.8625"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-19-a100095263ec>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m                           \u001b[0mworkers\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m                           \u001b[0mmax_queue_size\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m16\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m                           callbacks=[checkpoint,tb])\n\u001b[0m",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\legacy\\interfaces.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     89\u001b[0m                 warnings.warn('Update your `' + object_name + '` call to the ' +\n\u001b[1;32m     90\u001b[0m                               'Keras 2 API: ' + signature, stacklevel=2)\n\u001b[0;32m---> 91\u001b[0;31m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     92\u001b[0m         \u001b[0mwrapper\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_original_function\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\engine\\training.py\u001b[0m in \u001b[0;36mfit_generator\u001b[0;34m(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)\u001b[0m\n\u001b[1;32m   1416\u001b[0m             \u001b[0muse_multiprocessing\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0muse_multiprocessing\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1417\u001b[0m             \u001b[0mshuffle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshuffle\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1418\u001b[0;31m             initial_epoch=initial_epoch)\n\u001b[0m\u001b[1;32m   1419\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1420\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0minterfaces\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlegacy_generator_methods_support\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\engine\\training_generator.py\u001b[0m in \u001b[0;36mfit_generator\u001b[0;34m(model, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)\u001b[0m\n\u001b[1;32m    179\u001b[0m             \u001b[0mbatch_index\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    180\u001b[0m             \u001b[1;32mwhile\u001b[0m \u001b[0msteps_done\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0msteps_per_epoch\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m                 \u001b[0mgenerator_output\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnext\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput_generator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    182\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    183\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgenerator_output\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'__len__'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\keras\\utils\\data_utils.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    683\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    684\u001b[0m             \u001b[1;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_running\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 685\u001b[0;31m                 \u001b[0minputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mqueue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mblock\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    686\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mqueue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtask_done\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    687\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\multiprocessing\\pool.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    600\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    601\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 602\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    603\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mready\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    604\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mTimeoutError\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\multiprocessing\\pool.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    597\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    598\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mwait\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_event\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    600\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    601\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    547\u001b[0m             \u001b[0msignaled\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_flag\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    548\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0msignaled\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m                 \u001b[0msignaled\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_cond\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    550\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0msignaled\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    551\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Program Files\\Anaconda3\\lib\\threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    291\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m    \u001b[1;31m# restore state no matter what (e.g., KeyboardInterrupt)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    292\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 293\u001b[0;31m                 \u001b[0mwaiter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    294\u001b[0m                 \u001b[0mgotit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    295\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "parallel_model.optimizer.lr = 1e-6\n",
    "res = parallel_model.fit_generator(gen_train,\n",
    "                          steps_per_epoch =gen_train.num_samples()// batch_size,\n",
    "                          epochs = 150,\n",
    "                          validation_data=gen_test,\n",
    "                          validation_steps =gen_test.num_samples()//batch_size,\n",
    "                          verbose=1,\n",
    "                          initial_epoch=70,\n",
    "                          workers=4,\n",
    "                          max_queue_size=16,\n",
    "                          callbacks=[checkpoint,tb])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#model.load_weights('resent50-29.hdf5')\n",
    "parallel_model.load_weights('resent50-190219_BLINEAR-102.hdf5')\n",
    "model.save_weights('resent50-190219_BLINEAR-iou8604.hdf5')\n",
    "model.load_weights('resent50-190219_BLINEAR-iou8604.hdf5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "model.load_weights('resent50-190219_BLINEAR-iou8604.hdf5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'gen_test' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-b6ab4c190477>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mimages\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlables\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnext\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgen_test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'gen_test' is not defined"
     ]
    }
   ],
   "source": [
    "images,lables = next(gen_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np \n",
    "import os\n",
    "import tqdm\n",
    "#dir = r'C:\\jianweidata\\ocr\\psenet\\Extraction Test\\2x'\n",
    "dir = r'E:\\psenet-MTWI\\document\\mtwi_2018_task2_test\\icpr_mtwi_task2\\image_test'\n",
    "imagesfile = glob.glob(os.path.join(dir,'*.jpg'))\n",
    "MIN_LEN = 640\n",
    "MAX_LEN = 1024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████| 10000/10000 [32:16<00:00,  4.85it/s]\n"
     ]
    }
   ],
   "source": [
    "from tool.utils import ufunc_4 , scale_expand_kernels ,fit_minarearectange,fit_boundingRect,save_MTWI_2108_resault\n",
    "with tqdm.tqdm(total = len(imagesfile)) as bar:\n",
    "    for i,j in enumerate(imagesfile):\n",
    "                bar.update()\n",
    "                #j = r'E:\\psenet-MTWI\\document\\mtwi_2018_task2_test\\icpr_mtwi_task2\\image_test\\T1..67FbxfXXXXXXXX_!!0-item_pic.jpg.jpg'\n",
    "                images=cv2.imdecode(np.fromfile(j,dtype=np.uint8),-1) \n",
    "                #images=cv2.cvtColor(images,cv2.COLOR_RGB2BGR)\n",
    "                \n",
    "                h,w = images.shape[0:2]\n",
    "#                 if(h>w and h>MAX_LEN):\n",
    "#                     w = MAX_LEN / h * w   \n",
    "#                     h = MAX_LEN\n",
    "#                 elif(w>=h and w>MAX_LEN):\n",
    "#                     h = MAX_LEN / w * h   \n",
    "#                     w = MAX_LEN\n",
    "\n",
    "                if(w<h and w<MIN_LEN):\n",
    "                    h = MIN_LEN / w * h               \n",
    "                    w = MIN_LEN\n",
    "                elif(h<=w and h<MIN_LEN):\n",
    "                    w = MIN_LEN / h * w         \n",
    "                    h = MIN_LEN\n",
    "                    \n",
    "                w = min(w,MAX_LEN)    \n",
    "                h = min(h,MAX_LEN)\n",
    "                \n",
    "                \n",
    "                w = int(w //32 * 32)\n",
    "                h = int(h//32 * 32)\n",
    "                \n",
    "#                 w = 640\n",
    "#                 h = 640 \n",
    "                scalex = images.shape[1] / w\n",
    "                scaley = images.shape[0] / h\n",
    "                \n",
    "                images = cv2.resize(images,(w,h),cv2.INTER_AREA)\n",
    "                images = np.reshape(images,(1,h,w,3))            \n",
    "                \n",
    "                res = model.predict(images)\n",
    "                res1 = res[0]\n",
    "                res1[res1>0.9]= 1\n",
    "                res1[res1<=0.9]= 0\n",
    "                newres1 = []\n",
    "                for i in range(5):\n",
    "                    n = np.logical_and(res1[:,:,5],res1[:,:,i]) * 255\n",
    "                    newres1.append(n)\n",
    "                newres1.append(res1[:,:,5]*255)\n",
    "                num_label,labelimage = scale_expand_kernels(newres1)\n",
    "                rects = fit_minarearectange(num_label,labelimage)\n",
    "                \n",
    "                cv2.drawContours(images[0],np.array(rects)*2,-1,(0,0,255),2)\n",
    "                \n",
    "                base_name = '.'.join(os.path.basename(j).split('.')[:-1])\n",
    "                cv2.imwrite(os.path.join(dir,base_name+'_6.tif'),images[0])\n",
    "                \n",
    "                save_MTWI_2108_resault(os.path.join(dir,base_name+'.txt'),np.array(rects)*2,scalex ,scaley)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "MAX_LEN = 1440\n",
    "#images = cv2.imread('E:\\psenet-MTWI\\document\\mtwi_2018_task2_test\\icpr_mtwi_task2\\image_test\\T1._xuXoxqXXXz6E78_101916.jpg.jpg')\n",
    "images = cv2.imread('tt.jpg')\n",
    "h,w = images.shape[0:2]\n",
    "h,w = images.shape[0:2]\n",
    "\n",
    "\n",
    "if(w<h and w<MIN_LEN):\n",
    "    h = MIN_LEN / w * h               \n",
    "    w = MIN_LEN\n",
    "elif(h<=w and h<MIN_LEN):\n",
    "    w = MIN_LEN / h * w         \n",
    "    h = MIN_LEN\n",
    "\n",
    "w = min(w,MAX_LEN)    \n",
    "h = min(h,MAX_LEN)\n",
    "\n",
    "\n",
    "w = int(w //32 * 32)\n",
    "h = int(h//32 * 32)\n",
    "\n",
    "scalex = images.shape[1] / w\n",
    "scaley = images.shape[0] / h\n",
    "\n",
    "images = cv2.resize(images,(w,h),cv2.INTER_AREA)\n",
    "images = np.reshape(images,(1,h,w,3))    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1a736665d30>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZB4ko3kt+vzv0xuLkPHY+97V/KdercsRRTUJcQFwJdkcRNeYA3ukWsAsZ8YuN+SwwK2YL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sfHLuLwP/8v/gm7du2hSTXWGXZsX6CqEs8+/wyxafjMP/jchyh6W19QsSFW6p+VsTmlzLkzZ7jp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PwMVg2M7aR7NkMdmRXKrvOHgHK8efGcLO2zvbUjNMzMcnX1Kp1WA6U1n376CfVGk823G3T6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\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i2rSUsZo3YeK/4aatMeYvGGP+qTHmlTEmGGN+Y+B3mTHmvzTGfG6MOdPX/C/GmIWfeo+6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sQnPU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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a734df0dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(images[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 3.06 s\n"
     ]
    }
   ],
   "source": [
    "%time res = model.predict(images[0:1,:,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "res1 = res[0]\n",
    "res1[res1>0.5]= 1\n",
    "res1[res1<=0.5]= 0\n",
    "newres1 = []\n",
    "for i in range(5):\n",
    "#for i in [1,2,3]:\n",
    "    n = np.logical_and(res1[:,:,5],res1[:,:,i]) * 255\n",
    "    newres1.append(n)\n",
    "newres1.append(res1[:,:,5]*255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1a750b33da0>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5YGAgHThwgOLi4jLZvnPnDlWuXDnD8eZ7mxw4cIBZx6pZsyYdOHBAVR6MmDp1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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a734df86a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(newres1[5],cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "_,regions = cv2.connectedComponents(newres1[0].astype('uint8'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(720, 720)"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regions.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from tool.utils import ufunc_4 , scale_expand_kernels ,fit_minarearectange,fit_boundingRect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 102 ms\n",
      "Wall time: 112 ms\n",
      "[array([[211,  82],\n",
      "       [208,  72],\n",
      "       [333,  40],\n",
      "       [336,  50]], dtype=int64), array([[ 76, 116],\n",
      "       [ 74, 106],\n",
      "       [200,  74],\n",
      "       [202,  84]], dtype=int64), array([[306, 116],\n",
      "       [304, 106],\n",
      "       [369,  89],\n",
      "       [371,  99]], dtype=int64), array([[ 66, 119],\n",
      "       [ 64, 111],\n",
      "       [ 75, 108],\n",
      "       [ 77, 116]], dtype=int64), array([[149, 138],\n",
      "       [147, 129],\n",
      "       [235, 106],\n",
      "       [237, 115]], dtype=int64), array([[ 50, 124],\n",
      "       [ 47, 115],\n",
      "       [ 64, 111],\n",
      "       [ 66, 120]], dtype=int64), array([[161, 152],\n",
      "       [159, 142],\n",
      "       [298, 108],\n",
      "       [300, 118]], dtype=int64), array([[209, 154],\n",
      "       [206, 144],\n",
      "       [332, 113],\n",
      "       [335, 123]], dtype=int64), array([[  0, 141],\n",
      "       [ -2, 132],\n",
      "       [ 48, 114],\n",
      "       [ 51, 123]], dtype=int64), array([[  0, 168],\n",
      "       [ -2, 156],\n",
      "       [122, 118],\n",
      "       [125, 129]], dtype=int64), array([[  0, 154],\n",
      "       [ -2, 145],\n",
      "       [ 49, 128],\n",
      "       [ 52, 137]], dtype=int64), array([[ 30, 173],\n",
      "       [ 28, 163],\n",
      "       [145, 129],\n",
      "       [147, 139]], dtype=int64), array([[ 24, 208],\n",
      "       [ 21, 196],\n",
      "       [207, 142],\n",
      "       [210, 154]], dtype=int64), array([[  0, 204],\n",
      "       [ -3, 192],\n",
      "       [150, 142],\n",
      "       [155, 155]], dtype=int64), array([[244, 188],\n",
      "       [242, 178],\n",
      "       [356, 149],\n",
      "       [359, 160]], dtype=int64), array([[ 47, 221],\n",
      "       [ 44, 208],\n",
      "       [257, 151],\n",
      "       [261, 164]], dtype=int64), array([[259, 166],\n",
      "       [259, 154],\n",
      "       [269, 154],\n",
      "       [269, 166]], dtype=int64), array([[321, 184],\n",
      "       [319, 174],\n",
      "       [351, 165],\n",
      "       [354, 175]], dtype=int64), array([[167, 223],\n",
      "       [165, 213],\n",
      "       [311, 175],\n",
      "       [314, 186]], dtype=int64), array([[105, 226],\n",
      "       [102, 215],\n",
      "       [234, 180],\n",
      "       [237, 191]], dtype=int64), array([[340, 242],\n",
      "       [336, 231],\n",
      "       [446, 198],\n",
      "       [449, 209]], dtype=int64), array([[ 42, 262],\n",
      "       [ 39, 251],\n",
      "       [151, 216],\n",
      "       [154, 228]], dtype=int64), array([[  0, 267],\n",
      "       [ -4, 255],\n",
      "       [ 92, 217],\n",
      "       [ 96, 229]], dtype=int64), array([[ 82, 294],\n",
      "       [ 79, 282],\n",
      "       [303, 219],\n",
      "       [306, 231]], dtype=int64), array([[167, 247],\n",
      "       [156, 236],\n",
      "       [162, 229],\n",
      "       [173, 240]], dtype=int64), array([[269, 261],\n",
      "       [266, 250],\n",
      "       [339, 229],\n",
      "       [342, 240]], dtype=int64), array([[ 74, 274],\n",
      "       [ 71, 263],\n",
      "       [153, 239],\n",
      "       [156, 250]], dtype=int64), array([[162, 255],\n",
      "       [160, 243],\n",
      "       [175, 240],\n",
      "       [177, 252]], dtype=int64), array([[290, 271],\n",
      "       [287, 260],\n",
      "       [321, 252],\n",
      "       [324, 263]], dtype=int64), array([[  0, 353],\n",
      "       [ -6, 333],\n",
      "       [255, 243],\n",
      "       [262, 262]], dtype=int64), array([[  9, 279],\n",
      "       [  4, 270],\n",
      "       [ 28, 258],\n",
      "       [ 33, 267]], dtype=int64), array([[133, 315],\n",
      "       [129, 303],\n",
      "       [278, 262],\n",
      "       [281, 274]], dtype=int64), array([[238, 308],\n",
      "       [231, 297],\n",
      "       [241, 291],\n",
      "       [248, 303]], dtype=int64), array([[143, 338],\n",
      "       [140, 323],\n",
      "       [236, 300],\n",
      "       [239, 315]], dtype=int64), array([[238, 319],\n",
      "       [236, 305],\n",
      "       [253, 302],\n",
      "       [256, 316]], dtype=int64), array([[301, 324],\n",
      "       [292, 313],\n",
      "       [303, 304],\n",
      "       [312, 315]], dtype=int64), array([[  0, 370],\n",
      "       [ -5, 357],\n",
      "       [116, 305],\n",
      "       [122, 318]], dtype=int64), array([[157, 366],\n",
      "       [153, 353],\n",
      "       [299, 313],\n",
      "       [303, 326]], dtype=int64), array([[302, 333],\n",
      "       [300, 323],\n",
      "       [317, 319],\n",
      "       [320, 329]], dtype=int64), array([[466, 423],\n",
      "       [462, 410],\n",
      "       [574, 373],\n",
      "       [579, 387]], dtype=int64), array([[ 33, 447],\n",
      "       [ 27, 432],\n",
      "       [182, 374],\n",
      "       [187, 389]], dtype=int64), array([[145, 438],\n",
      "       [139, 421],\n",
      "       [239, 383],\n",
      "       [245, 399]], dtype=int64), array([[241, 413],\n",
      "       [234, 396],\n",
      "       [245, 392],\n",
      "       [252, 408]], dtype=int64), array([[167, 490],\n",
      "       [163, 476],\n",
      "       [411, 398],\n",
      "       [415, 412]], dtype=int64), array([[251, 427],\n",
      "       [245, 415],\n",
      "       [256, 409],\n",
      "       [263, 422]], dtype=int64), array([[489, 458],\n",
      "       [485, 444],\n",
      "       [596, 409],\n",
      "       [600, 422]], dtype=int64), array([[ 53, 561],\n",
      "       [ 47, 543],\n",
      "       [452, 408],\n",
      "       [458, 425]], dtype=int64), array([[251, 430],\n",
      "       [236, 423],\n",
      "       [238, 418],\n",
      "       [254, 424]], dtype=int64), array([[156, 464],\n",
      "       [152, 450],\n",
      "       [250, 420],\n",
      "       [254, 434]], dtype=int64), array([[256, 442],\n",
      "       [252, 426],\n",
      "       [269, 422],\n",
      "       [273, 438]], dtype=int64), array([[588, 442],\n",
      "       [588, 428],\n",
      "       [614, 428],\n",
      "       [614, 442]], dtype=int64), array([[491, 480],\n",
      "       [486, 466],\n",
      "       [571, 439],\n",
      "       [576, 452]], dtype=int64), array([[469, 511],\n",
      "       [464, 496],\n",
      "       [626, 441],\n",
      "       [631, 456]], dtype=int64), array([[ 59, 580],\n",
      "       [ 53, 562],\n",
      "       [404, 444],\n",
      "       [410, 462]], dtype=int64), array([[ 85, 591],\n",
      "       [ 80, 574],\n",
      "       [470, 447],\n",
      "       [475, 463]], dtype=int64), array([[118, 649],\n",
      "       [112, 632],\n",
      "       [639, 460],\n",
      "       [645, 477]], dtype=int64), array([[369, 519],\n",
      "       [365, 505],\n",
      "       [479, 469],\n",
      "       [484, 483]], dtype=int64), array([[540, 533],\n",
      "       [535, 518],\n",
      "       [653, 479],\n",
      "       [658, 493]], dtype=int64), array([[381, 538],\n",
      "       [376, 524],\n",
      "       [451, 500],\n",
      "       [456, 515]], dtype=int64), array([[309, 538],\n",
      "       [305, 523],\n",
      "       [356, 509],\n",
      "       [360, 524]], dtype=int64), array([[ 95, 680],\n",
      "       [ 90, 664],\n",
      "       [526, 521],\n",
      "       [532, 537]], dtype=int64), array([[184, 603],\n",
      "       [179, 587],\n",
      "       [376, 523],\n",
      "       [381, 539]], dtype=int64), array([[233, 564],\n",
      "       [229, 550],\n",
      "       [299, 527],\n",
      "       [304, 541]], dtype=int64), array([[ 73, 618],\n",
      "       [ 68, 603],\n",
      "       [220, 551],\n",
      "       [225, 565]], dtype=int64), array([[  0, 593],\n",
      "       [  0, 579],\n",
      "       [ 15, 579],\n",
      "       [ 15, 593]], dtype=int64), array([[ 81, 638],\n",
      "       [ 76, 623],\n",
      "       [170, 591],\n",
      "       [176, 606]], dtype=int64), array([[  0, 636],\n",
      "       [ -2, 622],\n",
      "       [ 24, 617],\n",
      "       [ 26, 632]], dtype=int64), array([[155, 731],\n",
      "       [150, 718],\n",
      "       [462, 616],\n",
      "       [466, 630]], dtype=int64), array([[244, 656],\n",
      "       [238, 640],\n",
      "       [299, 620],\n",
      "       [305, 636]], dtype=int64), array([[ 89, 659],\n",
      "       [ 83, 644],\n",
      "       [106, 635],\n",
      "       [112, 650]], dtype=int64), array([[  1, 659],\n",
      "       [ -1, 644],\n",
      "       [ 31, 637],\n",
      "       [ 34, 652]], dtype=int64), array([[103, 700],\n",
      "       [ 98, 684],\n",
      "       [224, 645],\n",
      "       [229, 660]], dtype=int64), array([[ 26, 673],\n",
      "       [ 26, 661],\n",
      "       [ 37, 661],\n",
      "       [ 37, 673]], dtype=int64), array([[  0, 682],\n",
      "       [  0, 668],\n",
      "       [  8, 668],\n",
      "       [  8, 682]], dtype=int64)]\n"
     ]
    },
    {
     "data": {
      "image/png": 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C0Bra+s3cDFPX5z5XNQDuDYWXeuqXZ2sYnL4OM9ZbbxuUnWFQuLsg+tRDWWmH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\nj5JFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a750b8c400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%time num_label,labelimage = scale_expand_kernels(newres1)\n",
    "%time rects = fit_minarearectange(num_label,labelimage)\n",
    "plt.imshow(labelimage)\n",
    "print(rects)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labelimage[90,50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[27, 23, 21],\n",
       "        [20, 18, 16],\n",
       "        [19, 17, 16],\n",
       "        ...,\n",
       "        [48, 77, 92],\n",
       "        [50, 79, 94],\n",
       "        [52, 78, 94]],\n",
       "\n",
       "       [[20, 20, 18],\n",
       "        [22, 22, 20],\n",
       "        [22, 23, 21],\n",
       "        ...,\n",
       "        [44, 74, 89],\n",
       "        [45, 75, 90],\n",
       "        [50, 79, 94]],\n",
       "\n",
       "       [[21, 24, 22],\n",
       "        [20, 23, 21],\n",
       "        [20, 23, 21],\n",
       "        ...,\n",
       "        [47, 77, 92],\n",
       "        [43, 74, 89],\n",
       "        [43, 74, 89]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[74, 78, 79],\n",
       "        [74, 78, 79],\n",
       "        [73, 78, 79],\n",
       "        ...,\n",
       "        [47, 73, 87],\n",
       "        [48, 74, 86],\n",
       "        [49, 75, 87]],\n",
       "\n",
       "       [[72, 76, 78],\n",
       "        [72, 75, 77],\n",
       "        [72, 77, 78],\n",
       "        ...,\n",
       "        [45, 71, 83],\n",
       "        [47, 73, 85],\n",
       "        [47, 74, 85]],\n",
       "\n",
       "       [[73, 77, 79],\n",
       "        [73, 77, 77],\n",
       "        [70, 75, 76],\n",
       "        ...,\n",
       "        [47, 73, 85],\n",
       "        [47, 73, 85],\n",
       "        [45, 73, 84]]], dtype=uint8)"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imagetest = np.copy(images[0])\n",
    "cv2.drawContours(imagetest,np.array(rects)*2,-1,(0,0,255),2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JC3NmEkVDdCAuictHVGrWQSKK95LHd4femJ2cx84zn/05uV6VPY5qEuIC4kqwO4qosQrg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YEPlUY5gjAU5UUQ4OIE4xy5ipyXTXpJpiWLsuwdhLPts2ouvfhIHn3i6bI6w7ms096tQ3feelpc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CtdHJEho8elTfYiNqIlUvwCFEjlYgwjR0VQ5zRTFZMogTCET3weXhs1BU+dmj7UUjOdwIw4So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AWl2byxhs72nbjpxp3ZYUITN/3hG1Qgh75jP1t40Lqey4qV+Vx3lbz/rX9aLMwla6inIcPa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\npLioNDVjsJw4ExMTZGXmMDMTpaNdzzDCoXT8fn8Kfvr9M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z6p9qTX/z9LN/O2pFJKzj/3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\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MEKoCs6SlqnNLQSLT6TRZnomt3NtM05zlxWiqFZIdtGqzCZ8LsbGl0x5yeuUi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DbCBGJ1brxaOgwCbBQTKy84U4ootoTGyDl2iD7AOYIwlAbCK7J1WODhNcgEATkFGLFp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\nQQFfCCEqggK+EEJUBAV8IYSoCD8AXkT2ZSkGE3cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a750c05e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(imagetest)\n",
    "cv2.imwrite('test2.jpg',imagetest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h = r'E:\\psenet-MTWI\\document\\mtwi_2018_task2_test\\icpr_mtwi_task2\\image_test\\LB1gXi2JVXXXXXUXFXXXXXXXXXX.jpg'\n",
    "images=cv2.imdecode(np.fromfile(h,dtype=np.uint8),-1) \n",
    "#images=cv2.cvtColor(images,cv2.COLOR_RGB2BGR)\n",
    "cv2.imwrite(r'E:\\tmp.jpg',images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-109-adbc9f38b16f>, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-109-adbc9f38b16f>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m    * 大概有100张图片没读出来 Y\u001b[0m\n\u001b[0m                    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "## todo\n",
    "* 大概有100张图片没读出来 Y\n",
    "* 把评测代码加上       \n",
    "* 换backone\n",
    "* 弧形文本行\n",
    "* 强交叉文本行\n",
    "* 误检太多"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
